This chapter identifies the possibilities of spatial knowledge extraction from unstructured text. Unstructured data does not necessarily require a more structured geography. But if these data are combined with other datasets that are geolocated, being able to geolocate these data might be useful. Translating text into geographic information is difficult. It is also a much more difficult proposition than simply assigning coordinates to photographs. The author introduces geoparsing, which is a process used to extract spatial data from texts. In addition to photos and videos, we can now geotag text messages, tweets, and more. But what about the data generated before the emergence of geoweb? Can we extract spatial information from old new articles? How can we add a spatial structure to data that do not already have it in order to mesh it with geoweb? Also, I am looking forward to knowing some useful tools for geoparsing.
Furthermore, this chapter doesn’t clarify what exactly the geoweb is. What are the boundaries between the web and geoweb? Last, many of the platforms that we rely on for geographic information are for-profit entities that do not have issues of justice and equity. However, it is important for us to note that how the geoweb encode, reify, and (re)produce inequality.